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Echo Sentiment — XLM Market Sentiment

$1.00 — buy_call_credits_bundle

buy_call_credits_bundle

PAID $1.00 per call (https://api.6766587364.lol/v1/bundle). Prepaid credit bundle: $1.00 buys 10 standard call credits (or 5 premium reports). Returns a bundle token to pass as bundle_token to other tools. Returns a payment requirement until called with a payment header, a prepaid bundle_token, or a free-tier api_key (mint one with get_free_api_key).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
api_keyNo
paymentNo
bundle_tokenNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. Added

TDQS

A3.8/5.0
Behavior4/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations present, the description carries the full burden of disclosure. It transparently states that the tool is paid, costs $1.00, returns a bundle_token, and demands a payment requirement until certain credentials are supplied. It does not cover edge cases such as idempotency or failed payments, but the core side effects are clearly disclosed.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is dense, front-loaded with the price, and every sentence contributes information. It is somewhat run-on and could be broken into clearer bullets, but it is compact and contains no filler.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a simple token-purchase tool with no output schema, the description covers the two possible return outcomes (bundle_token or payment requirement) and the credentials needed to avoid the payment requirement. The header-versus-parameter ambiguity and lack of explicit enterprise alternative leave a small gap, but the essential calling context is present.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 0%, so the description must add parameter meaning, and it largely does: bundle_token is described as a token to pass to other tools, api_key as a free-tier key obtainable from get_free_api_key, and payment as the required payment mechanism. The phrase 'payment header' is slightly inconsistent with the schema's `payment` parameter, which prevents a perfect score.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool's function: it sells a prepaid credit bundle where $1.00 buys 10 standard call credits or 5 premium reports and returns a bundle_token. This is a specific resource and outcome, but it does not explicitly differentiate itself from buy_enterprise_bundle beyond the price and token usage.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines3/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

It gives useful invocation context by explaining that a payment requirement is returned until the tool is called with a payment value, a prepaid bundle_token, or a free-tier api_key, and it even points to get_free_api_key. However, it does not explicitly state when to choose this tool over buy_enterprise_bundle or when not to use it, leaving alternative selection implied.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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